This proposal investigates the impacts of host vaccination and genetic disease resistance on pathogen ecology, transmission, and epidemiology. To do so, it integrates population scale in vivo experiments, field studies, and mathematical modeling; in a translational, wildlife and economically important, vertebrate host-multi-pathogen system: a virus and bacteria offish; with three aims. Aim 1: Develop and integrate mathematical and statistical models to infer the impacts of host vaccination and genetic disease resistance, on pathogen ecology, transmission, and epidemiology. Aim 2: Experimentally quantify single and multi-pathogen infection dynamics and transmission in vaccinated and genetically disease resistant hosts in vivo. Aim 3: Characterize pathogen ecology, transmission, and epidemiology in vaccinated and genetically disease resistant hosts through host population level laboratory and field experiments. Host vaccination and genetic enhancement for disease resistance are widespread strategies used to control infectious diseases in a range of human, wildlife, domesticated, and agricultural hosts. However, the impact of these practices on pathogen ecology and transmission is largely unknown. This is partly because protection efficacy is typically judged by disease reductions, without examining infection prevalence. Furthermore, there is virtually no information on how protection influences non-target pathogen species, or how natural heterogeneity in the level of pathogens that hosts are exposed to impacts efficacy. This is despite frequent observations that protection efficacy in the field is lower than predicted, potentially resulting in elevated disease severity. An understanding of these processes would enhance the development of vaccine and genetic enhancement regimes and improve the prospects of controlling current and future problematic infectious diseases. This project would develop much needed mathematical models to infer how vaccination and genetic resistance shape pathogen transmission under field conditions, in a host-pathogen system with many features that make it a highly translational model.